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Joint optimisation of price, warranty and recovery planning in remanufacturing of used products under linear and non-linear demand, return and cost functions

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  • Seyed Ahmad Yazdian
  • Kamran Shahanaghi
  • Ahmad Makui

Abstract

We investigate joint optimisation of remanufacturing, pricing and warranty decision-making for end-of-life products. A novel mathematical–statistical model is proposed where decisions involve pricing of returned used products (cores), degree of their remanufacturing, selling price and the warranty period for the final remanufactured products. The virtual age reliability improvement approach is chosen to model the upgrading of the cores to higher quality levels. We consider price- and warranty-dependent demand, price- and age-dependent return, and age-dependent remanufacturing cost in the model development. Both linear and non-linear forms of these functions are investigated. First, under some restrictive conditions of upgrade level and age distribution of received cores, special cases of the problem, which can be solved using a recently developed non-linear optimisation solver, are presented. We also implement a particle swarm optimisation algorithm for the solution of the original problem when all the restrictive assumptions are dropped. Finally, numerical experiments and sensitivity analysis are presented to address different aspects of the model and the solution approaches.

Suggested Citation

  • Seyed Ahmad Yazdian & Kamran Shahanaghi & Ahmad Makui, 2016. "Joint optimisation of price, warranty and recovery planning in remanufacturing of used products under linear and non-linear demand, return and cost functions," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(5), pages 1155-1175, April.
  • Handle: RePEc:taf:tsysxx:v:47:y:2016:i:5:p:1155-1175
    DOI: 10.1080/00207721.2014.915355
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    1. Chun Su & Xiaolin Wang, 2016. "Modeling flexible two-dimensional warranty contracts for used products considering reliability improvement actions," Journal of Risk and Reliability, , vol. 230(2), pages 237-247, April.
    2. Liu, Zhuojun & Diallo, Claver & Chen, Jing & Zhang, Michael, 2020. "Optimal pricing and production strategies for new and remanufactured products under a non-renewing free replacement warranty," International Journal of Production Economics, Elsevier, vol. 226(C).
    3. Luo, Ming & Wu, Shaomin, 2019. "A comprehensive analysis of warranty claims and optimal policies," European Journal of Operational Research, Elsevier, vol. 276(1), pages 144-159.
    4. Fei Zhang & Zailin Guan & Li Zhang & Yanyan Cui & Pengxing Yi & Saif Ullah, 2019. "Inventory management for a remanufacture-to-order production with multi-components (parts)," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 59-78, January.
    5. Y. Sarada & S. Sangeetha, 2022. "Coordinating a reverse supply chain with price and warranty dependent random demand under collection uncertainties," Operational Research, Springer, vol. 22(4), pages 4119-4158, September.
    6. Afsahi, Mohsen & Shafiee, Mahmood, 2020. "A stochastic simulation-optimization model for base-warranty and extended-warranty decision-making of under- and out-of-warranty products," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    7. Luo, Ming & Wu, Shaomin, 2018. "A value-at-risk approach to optimisation of warranty policy," European Journal of Operational Research, Elsevier, vol. 267(2), pages 513-522.
    8. Luo, Ming & Wu, Shaomin, 2018. "A mean-variance optimisation approach to collectively pricing warranty policies," International Journal of Production Economics, Elsevier, vol. 196(C), pages 101-112.

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